What is a churn flow, and how to build one
In this episode of Datadrivet, Joni Lindgren and Jasmin Yaya pick up the churn thread and look at the moment a customer hits cancel. The churn flow is what meets them there: the hosts describe it as a form with smart logic that engages customers who want to end their membership.
A good churn flow tries to do three things at once, and the hosts treat the balance between them as the real challenge:
- Make a genuine attempt to keep the customer.
- Keep the experience pleasant even for someone who is leaving.
- Collect feedback on why they’re going.
They offer three tips for building one. First, build a business case, so the work is justified by what churn actually costs. Second, keep the flow simple enough that customers move through it. Third, don’t make cancelling so easy that you give up retention attempts entirely.
To size the business case, they give a simple sum: take your monthly churn numbers and multiply by the average customer lifetime to see what each leaving customer is worth. That figure is what tells you how much effort the flow deserves. Netflix comes up as an example of a company with a churn flow, though the hosts don’t go into the specifics of how it works.
One honest open question the hosts wrestle with is ownership. It isn’t obvious whether a churn flow belongs to customer service, the product team, or communications, and they suggest a product manager may have to step up and champion it so it doesn’t fall between teams.
The takeaway: a churn flow is a chance to win the customer back, learn why they’re leaving, and leave a good last impression, but only if someone owns it and the business case is clear.
The hosts invite companies to share how they measure and reduce churn over on LinkedIn.
Listen to the full episode of Datadrivet for the full walkthrough. If you want to know whether your churn rate is normal for your model, that is what the benchmark tool is for: https://benchmark.scilla.studio
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Plot your retention, CAC payback, LTV:CAC and K-factor against the B2B and Consumer bands, and find out whether a good-looking number is real or sitting on a leaky retention curve.
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